[GRASS-user] v.class.mlR Error

[Jamille Haarloo]

Hello Moritz,

No worries. Thankful these modules are made available for newbies in RS
like me and also happy these interactions are possible for learning.
Hope to get back soon after some adjustments.

Best,
Jamille

On Thu, Jun 7, 2018 at 10:44 AM, Moritz Lennert <
mlennert at club.worldonline.be> wrote:

> Thanks
>
> On 07/06/18 15:17, Jamille Haarloo wrote:
>
>> The first 20+ lines of Stats_Training_Ben_test:
>>
>> cat,area,perimeter,compact_circle,compact_square,fd,WV_Benat
>> imofo_1_min,WV_Benatimofo_1_max,WV_Benatimofo_1_range,WV_B
>> enatimofo_1_mean,WV_Benatimofo_1_stddev,WV_Benatimofo_1_
>> variance,WV_Benatimofo_1_coeff_var,WV_Benatimofo_1_sum,
>> WV_Benatimofo_1_first_quart,WV_Benatimofo_1_median,WV_Bena
>> timofo_1_third_quart,WV_Benatimofo_2_min,WV_Benatimofo_2_
>> max,WV_Benatimofo_2_range,WV_Benatimofo_2_mean,WV_Benatimofo
>> _2_stddev,WV_Benatimofo_2_variance,WV_Benatimofo_2_
>> coeff_var,WV_Benatimofo_2_sum,WV_Benatimofo_2_first_quart,
>> WV_Benatimofo_2_median,WV_Benatimofo_2_third_quart,WV_Benati
>> mofo_3_min,WV_Benatimofo_3_max,WV_Benatimofo_3_range,WV_B
>> enatimofo_3_mean,WV_Benatimofo_3_stddev,WV_Benatimofo_3_
>> variance,WV_Benatimofo_3_coeff_var,WV_Benatimofo_3_sum,
>> WV_Benatimofo_3_first_quart,WV_Benatimofo_3_median,WV_Bena
>> timofo_3_third_quart,WV_Benatimofo_4_min,WV_Benatimofo_4_
>> max,WV_Benatimofo_4_range,WV_Benatimofo_4_mean,WV_Benatimofo
>> _4_stddev,WV_Benatimofo_4_variance,WV_Benatimofo_4_
>> coeff_var,WV_Benatimofo_4_sum,WV_Benatimofo_4_first_quart,
>> WV_Benatimofo_4_median,WV_Benatimofo_4_third_quart
>> 1144,3832.000000,1256.000000,5.723635,0.197144,1.729624,13,7
>> 6,63,46.4097077244259,9.98454911351384,99.69122100017,21.
>> 5139237092391,177842,40,47,53,40,138,98,90.2687891440501,15.
>> 2500825418009,232.565017531741,16.8940812061464,345910,81,
>> 92,100,15,61,46,40.8582985386221,7.82663897784868,61.2562776
>> 895802,19.1555675536767,156569,36,42,47,28,124,96,68.
>> 4253653444676,13.5774536655369,184.347248039801,19.
>> 8427200164517,262206,59,68,77
>> 1145,12092.000000,2282.000000,5.854120,0.192750,1.645226,13,
>> 94,81,51.386288455177,10.5294376761475,110.869057775874,20.
>> 4907534532914,621363,45,52,59,21,220,199,114.230731061859,
>> 23.3590328249442,545.644414516822,20.4489917973953,1381278,
>> 101,114,128,7,76,69,46.4219318557724,8.42747122371732
>> ,71.0222712265835,18.1540726264915,561334,42,48,52,17,198,
>> 181,97.2732385047966,22.492313569247,505.904169697333,
>> 23.1228176577445,1176228,84,97,110
>>
>> [...]
>
> ---------------------
>> All the lines of the output of v.db.select Training_Ben2 at haarlooj_Ben_Tes
>> t:
>>
>> cat|id|Type|code
>> 1|4|B29|18
>> 2|5|B31|19
>> 3|3|B28|17
>>
>
>
> Again a lack of clear documentation on my side: both the training and the
> segment info should contain the same attributes, with only additional one
> column ('code' in your case) present in the training data.
>
> It should be possible to do this differently, i.e. provide the module with
> the features of all segments, and only the id/cat of each training segment
> with the relevant class and have the module merge the two, but this is not
> implemented, yet.
>
> I also just notice that you have the word 'Training' in both names.
>
> The segment_file/segment_map contains the info (cat + all feature
> variables) of all segments you wish to classify, either in the form of a
> csv file or in the form of a vector map with the info in the attribute
> table.
>
> The training_file/training_map contains the info (cat + all feature
> variables + class) of the training data. Often this is an extract of the
> former, but not necessarily.
>
> All columns in the training file have to be present in the segment file,
> except for the class column (your 'code').
>
> Sorry for the lack of docs. This module has mostly been used internally
> here and so we are not always aware of the unclear and missing parts.
> Having your feedback has been very useful !
>
> Moritz
>
>
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